为组织员工健康倡议制定质量改善实施分类学
Grace Gao1,2,3, Lindsay Vaclavik4, Alvin D Jeffery5,6,7
1Veteran Affairs Quality Scholars Program, Joseph Maxwell Cleland Atlanta VA Medical Center, Atlanta, Georgia, United States.
一个新的质量改进和实施分类法 (QIIT) 标准化了基于证据的实践障碍和促进者的分类. 这种语义方法增强了可持续医疗保健创新的知识代表性.
科学领域:
- 医疗信息学 医疗信息学
- 实施科学 实施科学
- 知识管理知识管理
背景情况:
- 标准化分类学 (STs) 对医疗保健知识表示和互操作性至关重要.
- 在将证据转化为质量改进 (QI) 实施障碍和促进者的分类方面存在差距.
- 本报告引入了一种新的语义和本体学方法来解决这一差距.
研究的目的:
- 利用语义和本体学的方法,从员工健康QI计划中综合实施障碍和促进器数据.
- 引入一个原始的框架,即质量改进和实施分类法 (QIIT),用于在QI过程中分类实施障碍和促进者.
主要方法:
- 通过因果分析和定性主题分析,从QI障碍和促进者数据集中合成了术语.
- 开发了质量改进和实施分类学 (QIIT) 分类方案.
- 在QI阶段,实施研究领域和因果类别的现有术语上构建了QIIT.
主要成果:
- 该QIIT是一个层次和关系分类方案.
- 分类学链接到QI阶段,实施领域和概念决定因素.
- 它包括可自定义的描述符和属性尺度,用于详细分析.
结论:
- 引入了一种新的方法来标准化描述证据翻译到QI实现的分类学.
- QIIT分类方案减少了冗余,并使语义协议和本体知识表示成为可能.
- 整合现有的分类学增强了重复使用,并支持可比,可共享的QI评估,以实现可持续实施.
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